An infrared ceiling sensor network system is reported in this study to realize behavior analysis and fall detection of a single person in the home environment. The sensors output multiple binary sequences from which we know the existence/non-existence of persons under the sensors. The short duration averages of the binary responses are shown to be able to be regarded as pixel values of a top-view camera, but more advantageous in the sense of preserving privacy. Using the “pixel values” as features, support vector machine classifiers succeeded in recognizing eight activities (walking, reading, etc.) performed by five subjects at an average recognition rate of 80.65%. In addition, we proposed a martingale framework for detecting falls in this system. The experimental results showed that we attained the best performance of 95.14% (F1 value), the FAR of 7.5% and the FRR of 2.0%. This accuracy is not sufficient in general but surprisingly high with such low-level information. In summary, it is shown that this system has the potential to be used in the home environment to provide personalized services and to detect abnormalities of elders who live alone.

Objectives: To characterize gait disorders in patients with amnestic mild cognitive impairment (aMCIs) and determine the association between the performance of the gait function and cognition. Methodology: In this study, we enrolled 38 patients with aMCI and 30 cognitively normal individuals normal controls (NC). Neuropsychological assessments included tests of memory, executive function, language, and attention. Using an inertial-sensor-based wearable instrument, we collected the gait data dynamically for at least 1 h/day for 2 weeks. The gait parameters included walking velocity, stride length, stride time, cadence, and stride time variability. Results: The aMCI patients had reduced walking velocity and stride length and increased stride time variability compared with the NCs. The total number of steps, stride time, and cadence did not differ between the two groups. For all the subjects, walking velocity and stride length was positively associated with memory and executive function. Stride time variability was negatively correlated with the cognitive domains including memory, executive function and attention. Conclusion: This study suggested that cognitive impairment-related gait disorders occur (reduced gait speed, gait length, and gait stability) in daily life walking among the aMCI patients. A sensor-based wearable device for gait measurement may be an alternative and convenient tool for screening cognitive impairment.

Low-cost sensor networks for multitarget tracking are increasingly becoming important equipment in many applications. A major problem is that these sensors usually provide only a binary response in each epoch, if a target is present or absent. Efficient approaches for realizing the location and tracking of multiple targets are needed. In this paper, we develop a soft tracking system using an infrared ceiling sensor network and propose a novel algorithm for tracking multiple people. In this system, 43 infrared sensors were attached to the ceiling of an office room (15.0 m × 8.5 m). Some pieces of weak evidence such as locations of personal desks, and the moving directions of people, were used for soft tracking. Through experiments, the ability of tracking in different situations was evaluated. The tracking accuracy during a 3 h period was investigated. The results showed that this system was able to track up to eight people simultaneously for hours in an office room. The tracking accuracy was above 90% most of the time, although some identity ambiguities occurred.

The heterogeneity of tumor clones drives the selection and evolution of distinct tumor cell populations, resulting in an intricate and dynamic tumor evolution process. While tumor bulk DNA sequencing helps elucidate intratumor heterogeneity, challenges such as the misidentification of mutation multiplicity due to copy number variations and uncertainties in the reconstruction process hinder the accurate inference of tumor evolution. In this study, we introduce a novel approach, REconstructing Tumor Clonal Heterogeneity and Evolutionary Relationships (RETCHER), which characterizes more realistic cancer cell fractions by accurately identifying mutation multiplicity while considering uncertainty during the reconstruction process and the credibility and reasonableness of subclone clustering. This method comprehensively and accurately infers multiple forms of tumor clonal heterogeneity and phylogenetic relationships. RETCHER outperforms existing methods on simulated data and infers clearer subclone structures and evolutionary relationships in real multisample sequencing data from five tumor types. By precisely analysing the complex clonal heterogeneity within tumors, RETCHER provides a new approach to tumor evolution research and offers scientific evidence for developing precise and personalized treatment strategies. This approach is expected to play a significant role in tumor evolution research, clinical diagnosis, and treatment. RETCHER is available for free at https://github.com/zlsys3/RETCHER.